Texture Analysis and Cartographic Feature Extraction.

Abstract

Investigations into using various image descriptors as well as developing interactive feature extraction software on the Digital Image Analysis Laboratory(DIAL) have culminated in a revised procedure to test statistical classification methods. An interactive experiment using this procedure was performed and showed that of the image descriptors tested, the most significant was a two component vector derived from an average and a standard deviation measure of gray shades. The texture measures failed to deliver any increase in performance for the classifier. In general, this report shows that statistical classification methods are insufficient by themselves to deliver the performance needed in a semi-automated cartographic feature extraction system. Originator-supplied keywords: Ad-Hoc image descriptor; Bayes classifier; Bhattachryya distance; Clustering; Digital Image Analysis Laboratory (DIAL); Feature extraction; Interactive processing; Laws texture measure; Principal components; Raster processing; Relaxation.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1985
Accession Number
ADA159220

Entities

People

  • R. S. Rand

Organizations

  • Geospatial Research Laboratory

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Composite Images
  • Computer Science
  • Computers
  • Data Analysis
  • Data Modeling
  • Digital Image Processing
  • Digital Images
  • Feature Extraction
  • Image Processing
  • Image Segmentation
  • Information Science
  • Machine Learning
  • Mainframe Computers
  • Sequences
  • Statistics
  • Supervised Machine Learning

Readers

  • Computer Vision.
  • Software Engineering

Technology Areas

  • AI & ML